Web manufacturing refers to production and/or processing of long, thin sheets of bendable, flexible and/or soft material, in particular paper, cardboard, textile, plastic film, foil, (sheet) metal, and sometimes wire, commonly referred to as web. During production or processing, a web is generally transported over rollers in a moving direction. Between processing stages, webs may be stored and transported as rolls also referred to as coils, packages and doffs. A final result of web manufacturing usually comprises sheets being separated from the web by cutting or otherwise separating in a cross direction perpendicular to the moving direction. A main reason for work with webs instead of sheets is economics. Webs, being continuous, may generally be produced and/or processed at higher speeds than sheets, without start-stop issues which are inherent to production and/or processing of sheets.
For supervision and/or quality control of web manufacturing, web inspection systems, as described e.g. in US 2002/0110269 A1, are frequently applied which use digital imaging techniques, in particular image capture and image processing, for detecting defects or other anomalies. For web manufacturing of paper or cardboard, holes, spots and dirt particles are examples of strong defects, frequently briefly referred to as defects, whereas wrinkles, streaks and slime spots are examples of weak defects. Correspondingly, for web manufacturing of sheet metal makers, slag inclusions, cracks and scratches are examples of strong defects whereas weak cracks, weak scratches and indentations are examples of weak defects.
Defects give rise to local deviations of various characteristic image quantities, in particular of a pixel intensity level, from average and/or expected values. In the above examples, weak defects cause only a slight change in an intensity level of the digital video signal as compared to a mean variation of the intensity level measured from a faultless product. Strong defects, on the other hand, give generally rise to substantial deviations.
In paper and pulp making, dirt particles can reduce the quality of the product significantly. Currently available web inspections systems (WIS) for defect detection can possibly count less than 500 dirt particles per second per system and classify them based on their sizes. In such a situation, current systems are not capable of doing anything else for example detecting other kinds of defects.
A performance of currently available web inspection systems is not high enough to allow for classifying dirt particles online, i.e. in real-time, while simultaneously supporting full web measurement. Current solutions for the pulp and paper dirt analysis are based on snapshot images, limited cross direction (CD) band or scanning imaging methods; or they are not supporting really high dirt densities, i.e. dirt densities of over 1000, let alone over 10000 dirt particles per second, and thus are not capable of supporting full web coverage and very high density dirt analysis in real time.
One of the most beneficial supervision and/or quality control procedures is dirt counting and dirt area classification, which analyzes the content of foreign materials in the web. Several international standards have been published for the dirt analysis procedure, but most of them represent offline laboratory measurements and produce test reports of only a small portion of the area of the manufactured pulp, paper, or paperboard product. ISO 5350 standard consists of four parts, under the general title “Pulps—Estimation of dirt and shives”. The first two parts include transmission light based test procedures for laboratory sheets and mill sheeted pulp. Parts 3 and 4 are based on reflection measurement and Equivalent Black Area (EBA) method. Part 3 presents the visual inspection and Part 4 the instrumental inspection test methods. Also Tappi organization has published several Dirt analysis standards. Tappi T213 om-01 “Dirt in pulp—chart method” provides a test method for estimating the amount of dirt in pulp based on equivalent black area (EBA). In T213 a dirt speck is defined as the area of a round black spot on a white background of the TAPPI Dirt Estimation Chart. Tappi T 563 “Equivalent Black Area (EBA) and Count of Visible Dirt in Pulp, Paper, and Paperboard by Image Analysis” presents a method that uses image analysis to determine the level of dirt in pulp, paper, and paperboard based on EBA of dirt specks within the physical area range of 0.02 to 3.0 mm2 reported in parts per million and the number of dirt specks per square meter.
Another quality factor in papermaking, but also for some other web products like for example pulp or glass fiber, is formation. Certain kinds of formation irregularities, e.g. non-uniform fiber clusters, are causing so-called flocs (which appear as cloudiness when looking through the product). Also in some web manufacturing products, formation irregularities are present in the form of uneven surfaces like for example coated paper with mottling, which can lead to unwanted, uneven print density and color variations. Earlier solutions for the paper or surface formation floc analysis were based on snapshot images, narrow band or scanning imaging methods and thus not capable of covering the whole web in real-time.
A performance of currently available web inspection systems is not sufficient for allowing for online, i.e. real-time, floc analysis including calculation of floc size distribution, while supporting full web measurement, i.e. analysis over the whole cross direction of the web.